Statistical Optimality of Interpolated Nearest Neighbor Algorithms. - Yue Xing 002; Qifan Song; Guang Cheng 003 (CoRR, 2018)

Directional Pruning of Deep Neural Networks. - Shih-Kang Chao; Zhanyu Wang; Yue Xing 002; Guang Cheng 003 (NeurIPS, 2020)

Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. - Yue Xing 002; Qifan Song; Guang Cheng 003 (AISTATS, 2021)

On the Generalization Properties of Adversarial Training. - Yue Xing 002; Qifan Song; Guang Cheng 003 (AISTATS, 2021)

Adversarially Robust Estimate and Risk Analysis in Linear Regression. - Yue Xing 002; Ruizhi Zhang; Guang Cheng 003 (AISTATS, 2021)

On the Algorithmic Stability of Adversarial Training. - Yue Xing 002; Qifan Song; Guang Cheng 003 (NeurIPS, 2021)

Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. - Yue Xing 002; Qifan Song; Guang Cheng 003 (AISTATS, 2022)

Why Do Artificially Generated Data Help Adversarial Robustness. - Yue Xing 002; Qifan Song; Guang Cheng 003 (NeurIPS, 2022)

Phase Transition from Clean Training to Adversarial Training. - Yue Xing 002; Qifan Song; Guang Cheng 003 (NeurIPS, 2022)

Benefit of Interpolation in Nearest Neighbor Algorithms. - Yue Xing 002; Qifan Song; Guang Cheng 003 (SIAM J. Math. Data Sci., 2022)

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. - Yingqian Cui; Jie Ren 019; Yuping Lin; Han Xu 002; Pengfei He; Yue Xing 002; Wenqi Fan; Hui Liu 031; Jiliang Tang (CoRR, 2023)

Confidence-driven Sampling for Backdoor Attacks. - Pengfei He; Han Xu 002; Yue Xing 002; Jie Ren 019; Yingqian Cui; Shenglai Zeng; Jiliang Tang; Makoto Yamada; Mohammad Sabokrou (CoRR, 2023)

Distributed Censored Quantile Regression. - Tony Sit; Yue Xing 002 (J. Comput. Graph. Stat., 2023)

Exploring Memorization in Fine-tuned Language Models. - Shenglai Zeng; Yaxin Li 001; Jie Ren 019; Yiding Liu; Han Xu 002; Pengfei He; Yue Xing 002; Shuaiqiang Wang; Jiliang Tang; Dawei Yin (ACL (1), 2024)

The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). - Shenglai Zeng; Jiankun Zhang; Pengfei He; Yiding Liu; Yue Xing 002; Han Xu 002; Jie Ren 019; Yi Chang 001; Shuaiqiang Wang; Dawei Yin; Jiliang Tang (ACL (Findings), 2024)

Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. - Yue Xing 002; Xiaofeng Lin 005; Qifan Song; Yi Xu 011; Belinda Zeng; Guang Cheng 003 (AISTATS, 2024)

Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. - Rajdeep Haldar; Yue Xing 002; Qifan Song (AISTATS, 2024)

Unveiling and Mitigating Memorization in Text-to-Image Diffusion Models Through Cross Attention. - Jie Ren 019; Yaxin Li 001; Shenglai Zeng; Han Xu 002; Lingjuan Lyu; Yue Xing 002; Jiliang Tang (ECCV (77), 2024)

Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis. - Yuping Lin; Pengfei He; Han Xu 002; Yue Xing 002; Makoto Yamada; Hui Liu 031; Jiliang Tang (EMNLP, 2024)

Superiority of Multi-Head Attention in In-Context Linear Regression. - Yingqian Cui; Jie Ren 019; Pengfei He; Jiliang Tang; Yue Xing 002 (CoRR, 2024)

Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data. - Yue Xing 002; Xiaofeng Lin 005; Namjoon Suh; Qifan Song; Guang Cheng 003 (CoRR, 2024)

EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations. - Jie Ren 019; Yingqian Cui; Chen Chen 043; Vikash Sehwag; Yue Xing 002; Jiliang Tang; Lingjuan Lyu (CoRR, 2024)

Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data. - Shenglai Zeng; Jiankun Zhang; Pengfei He; Jie Ren 019; Tianqi Zheng; Hanqing Lu; Han Xu 002; Hui Liu 031; Yue Xing 002; Jiliang Tang (CoRR, 2024)

Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models. - Jie Ren 019; Kangrui Chen; Yingqian Cui; Shenglai Zeng; Hui Liu 031; Yue Xing 002; Jiliang Tang; Lingjuan Lyu (CoRR, 2024)

Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility. - Rajdeep Haldar; Yue Xing 002; Qifan Song; Guang Lin 001 (CoRR, 2024)

Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study. - Pengfei He; Yingqian Cui; Han Xu 002; Hui Liu 031; Makoto Yamada; Jiliang Tang; Yue Xing 002 (CoRR, 2024)

Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models. - Jie Ren 019; Kangrui Chen; Chen Chen 043; Vikash Sehwag; Yue Xing 002; Jiliang Tang; Lingjuan Lyu (CoRR, 2024)

Make LLMs better zero-shot reasoners: Structure-orientated autonomous reasoning. - Pengfei He; Zitao Li; Yue Xing 002; Yaling Li; Jiliang Tang; Bolin Ding (CoRR, 2024)

Stealthy Backdoor Attack via Confidence-driven Sampling. - Pengfei He; Yue Xing 002; Han Xu 002; Jie Ren 019; Yingqian Cui; Shenglai Zeng; Jiliang Tang; Makoto Yamada; Mohammad Sabokrou (Trans. Mach. Learn. Res., 2024)

An Adversarially Robust Formulation of Linear Regression With Missing Data. - Alireza Aghasi; Saeed Ghadimi; Yue Xing 002; MohammadJavad Feizollahi (IEEE Trans. Signal Process., 2024)

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. - Yingqian Cui; Jie Ren 019; Yuping Lin; Han Xu 002; Pengfei He; Yue Xing 002; Lingjuan Lyu; Wenqi Fan; Hui Liu 031; Jiliang Tang (SIGKDD Explor., 2024)

DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models. - Yingqian Cui; Jie Ren 019; Han Xu 002; Pengfei He; Hui Liu 031; Lichao Sun 001; Yue Xing 002; Jiliang Tang (SIGKDD Explor., 2024)

A General Framework to Enhance Fine-tuning-based LLM Unlearning. - Jie Ren 019; Zhenwei Dai; Xianfeng Tang; Hui Liu; Jingying Zeng; Zhen Li; Rahul Goutam; Suhang Wang; Yue Xing 002; Qi He 002 (ACL (Findings), 2025)

Unveiling Privacy Risks in LLM Agent Memory. - Bo Wang 069; Weiyi He; Shenglai Zeng; Zhen Xiang; Yue Xing 002; Jiliang Tang; Pengfei He (ACL (1), 2025)

Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models. - Yingqian Cui; Pengfei He; Jingying Zeng; Hui Liu 003; Xianfeng Tang; Zhenwei Dai; Yan Han 001; Chen Luo 003; Jing Huang; Zhen Li; Suhang Wang; Yue Xing 002; et al. (ACL (Findings), 2025)

Red-Teaming LLM Multi-Agent Systems via Communication Attacks. - Pengfei He; Yuping Lin; Shen Dong; Han Xu 002; Yue Xing 002; Hui Liu 031 (ACL (Findings), 2025)

Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach. - Shenglai Zeng; Pengfei He; Kai Guo 003; Tianqi Zheng; Hanqing Lu; Yue Xing 002; Hui Liu 031 (ACL (1), 2025)

A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration. - Yingqian Cui; Pengfei He; Xianfeng Tang; Qi He 002; Chen Luo 003; Jiliang Tang; Yue Xing 002 (AISTATS, 2025)

Superiority of Multi-Head Attention: A Theoretical Study in Shallow Transformers in In-Context Linear Regression. - Yingqian Cui; Jie Ren 019; Pengfei He; Hui Liu 031; Jiliang Tang; Yue Xing 002 (AISTATS, 2025)

Six-CD: Benchmarking Concept Removals for Text-to-image Diffusion Models. - Jie Ren 019; Kangrui Chen; Yingqian Cui; Shenglai Zeng; Hui Liu 003; Yue Xing 002; Jiliang Tang; Lingjuan Lyu (CVPR, 2025)

Data Poisoning for In-context Learning. - Pengfei He; Han Xu 002; Yue Xing 002; Hui Liu 031; Makoto Yamada; Jiliang Tang (NAACL (Findings), 2025)

Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective. - Shenglai Zeng; Jiankun Zhang; Bingheng Li; Yuping Lin; Tianqi Zheng; Dante Everaert; Hanqing Lu; Hui Liu 031; Yue Xing 002; Monica Xiao Cheng; Jiliang Tang (NAACL (Long Papers), 2025)

Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Model. - Jie Ren 019; Kangrui Chen; Chen Chen 043; Vikash Sehwag; Yue Xing 002; Jiliang Tang; Lingjuan Lyu (WWW, 2025)

LLM Safety Alignment is Divergence Estimation in Disguise. - Rajdeep Haldar; Ziyi Wang; Qifan Song; Guang Lin 001; Yue Xing 002 (CoRR, 2025)

Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models. - Yingqian Cui; Pengfei He; Jingying Zeng; Hui Liu 003; Xianfeng Tang; Zhenwei Dai; Yan Han 001; Chen Luo 003; Jing Huang; Zheng Li 018; Suhang Wang; Yue Xing 002; et al. (CoRR, 2025)

Multi-Faceted Studies on Data Poisoning can Advance LLM Development. - Pengfei He; Yue Xing 002; Han Xu 002; Zhen Xiang; Jiliang Tang (CoRR, 2025)

Red-Teaming LLM Multi-Agent Systems via Communication Attacks. - Pengfei He; Yupin Lin; Shen Dong; Han Xu 002; Yue Xing 002; Hui Liu 031 (CoRR, 2025)

A General Framework to Enhance Fine-tuning-based LLM Unlearning. - Jie Ren 019; Zhenwei Dai; Xianfeng Tang; Hui Liu 003; Jingying Zeng; Zhen Li; Rahul Goutam; Suhang Wang; Yue Xing 002; Qi He 002 (CoRR, 2025)

Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy. - Jie Ren 019; Zhenwei Dai; Xianfeng Tang; Yue Xing 002; Shenglai Zeng; Hui Liu 031; Jingying Zeng; Qiankun Peng; Samarth Varshney; Suhang Wang; Qi He 002; Charu C. Aggarwal; et al. (CoRR, 2025)

Comprehensive Vulnerability Analysis is Necessary for Trustworthy LLM-MAS. - Pengfei He; Yue Xing 002; Shen Dong; Juanhui Li; Zhenwei Dai; Xianfeng Tang; Hui Liu 031; Han Xu 002; Zhen Xiang; Charu C. Aggarwal; Hui Liu 031 (CoRR, 2025)

Attention Knows Whom to Trust: Attention-based Trust Management for LLM Multi-Agent Systems. - Pengfei He; Zhenwei Dai; Xianfeng Tang; Yue Xing 002; Hui Liu 003; Jingying Zeng; Qiankun Peng; Shrivats Agrawal; Samarth Varshney; Suhang Wang; Jiliang Tang; Qi He 002 (CoRR, 2025)

SoK: Machine Unlearning for Large Language Models. - Jie Ren 019; Yue Xing 002; Yingqian Cui; Charu C. Aggarwal; Hui Liu 031 (CoRR, 2025)